<content> Draw-Descriptions (Maxima) </content>

490c07d7-977a-4be0-a0cc-45603502fd78 34 Валерий Очков Martin Kraska 3 5 false true 0 7 decimal

&[DATE] &[TIME] - &[FILENAME]

Расчет термического КПД паротурбинной установки с двумя регенеративными подогревателями

p.0 130 atm * :

T.0 540 °C * :

Параметры ПТУ

p.K 30 mmHg * :

p.0 T.0 p.1 p.2 p.K η.T wf H2O : T.K T P p.K Q 0.5 wf CoolProp_Props : h'.KH H T T.K Q 0 wf CoolProp_Props : s.KH S T T.K Q 0 wf CoolProp_Props : 13 mat T'.H2 T P p.2 Q 0.5 wf CoolProp_Props : h'.H2 H T T'.H2 Q 0 wf CoolProp_Props : s.H2 S T T'.H2 Q 0 wf CoolProp_Props : 13 mat T'.H1 T P p.1 Q 0.5 wf CoolProp_Props : h'.H1 H T T'.H1 Q 0 wf CoolProp_Props : s.H1 S T T'.H1 Q 0 wf CoolProp_Props : 13 mat T.ΠB T P p.0 S s.H1 wf CoolProp_Props : h''.H2 H P p.2 S s.H2 wf CoolProp_Props : 12 mat h.0 H P p.0 T T.0 wf CoolProp_Props : s S P p.0 T T.0 wf CoolProp_Props : h.K H P p.K S s wf CoolProp_Props : 13 mat h.1 H P p.1 S s wf CoolProp_Props : h.2 H P p.2 S s wf CoolProp_Props : h.ΠB H P p.0 S s.H1 wf CoolProp_Props : 13 mat T''.H2 T P p.2 S s.H2 wf CoolProp_Props : h''.KH H P p.2 S s.KH wf CoolProp_Props : 12 mat α.1 α.2 21 mat α.1 h.1 * 1 α.1 - (h''.H2 * + 1 h'.H1 * ≡ α.2 h.2 * 1 α.1 - α.2 - (h''.KH * + 1 α.1 - (h'.H2 * ≡ 21 mat α.1 α.2 21 mat roots : l.01 1 h.0 h.1 - (* : l.12 1 α.1 - (h.1 h.2 - (* : l.2K 1 α.1 - α.2 - (h.2 h.K - (* : 13 mat l.KH 1 α.1 - α.2 - (h''.KH h'.KH - (* : l.H2 1 α.1 - (h''.H2 h'.H2 - (* : 12 mat l.ΠH 1 h.ΠB h'.H1 - (* : q 1 h.0 h.ΠB - (* : 12 mat l.01 l.12 + l.2K + l.KH - l.H2 - l.ΠH - q / 131 line :

p.0 T.0 p.0 p.0 p.K η.T % 43.88

p.0 T.0 p.K p.K p.K η.T % 43.88

p.0 T.0 30 atm * 30 atm * p.K η.T % 46.82

p.0 T.0 70 atm * 30 atm * p.K η.T % 47.45

p p.0 p.K p.0 p.0 p.K - 200 / - range :

p atm / p.0 T.0 70 atm * p p.K η.T vectorize % / augment p atm / p.0 T.0 p 30 atm * p.K η.T vectorize % / augment

Один отбор пара - параметрический график

T P p Q 0 H2O CoolProp_Props vectorize °C / p.0 T.0 p p p.K η.T vectorize % / augment

n 20 :

p.12 10 atm * :

p.1.min p.12 :

p.1.max 132 atm * :

p.2.min 0.5 atm * :

p.2.max p.12 :

j 1 n 1 + (range k 1 n 1 + (range p.1 p.1.min n 1 + j - n / * p.1.max j 1 - n / * + : p.2 p.2.min n 1 + k - n / * p.2.max k 1 - n / * + : M j k el p.0 T.0 p.1 p.2 p.K η.T : 31 line for for

p.0 T.0 33 atm * 2.8 atm * p.K η.T 0.48676

<content> Draw-Descriptions (Maxima) </content> <content> Draw-Descriptions (Maxima) </content>

dOptionen

Options

[Maxima Draw] adapt_depth (=10): maximale Teilungstiefe der adaptive Kurvenabtastung. [Maxima Draw] adapt_depth (=10): maximum number of adaptive interval splits when drawing curves. addapt_depth adapt_depth :

[Maxima Draw3D] axis_3d (=true): Achsen zeichnen, false: keine Achsen zeichnen. Globale Option. [Maxima Draw3D] axis_3d (=true): draw axes, false: don't draw axes. Global option. axis_3d axis_3d :

[Maxima Draw2D] axis_bottom (=true): untere Achse zeichnen, false: Achse nicht zeichnen. Globale Option. [Maxima Draw2D]  axis_bottom (=true): draw bottom axis, false: don't draw axis. Global option. axis_bottom axis_bottom :

[Maxima Draw2D] axis_top (=true): obere Achse zeichnen, false: Achse nicht zeichnen. Globale Option. [Maxima Draw2D] axis_top (=true): draw top axis, false: don't draw axis. Global option. axis_top axis_top :

[Maxima Draw2D] axis_left (=true): linke Achse zeichnen, false: Achse nicht zeichnen. Globale Option. [Maxima Draw2D] axis_left (=true): draw left axis, false: don't draw axis. Global option. axis_left axis_left :

[Maxima Draw2D] axis_right (=true): rechte Achse zeichnen, false: Achse nicht zeichnen. Globale Option. [Maxima Draw2D] axis_right (=true): draw right axis, false: don't draw axis. Global option. axis_right axis_right :

[Maxima Draw] background_color (=white): Hintergrundfarbe des Diagramms. Globale Option. [Maxima Draw] background_color (=white): background color of the plot. Global option. background_color background_color :

[Maxima Draw] border (=true): Ränder von polygon(), ellipse(), quadrilateral(), triangle() oder rectangle() zeichnen. [Maxima Draw] border (=true): draw borders of polygon(), ellipse(), quadrilateral(), triangle() or rectangle()objects. border border :

[Maxima Draw3D] capping(=false): Endflächen an tube()-Objekten, false, true oder Liste mit zwei Werten. [Maxima Draw3D] capping (=false): indicates if extremes of the tube object remain open (false) or are closed (true). If only one end is to be closed, provide a list with two entries. capping capping :

[Maxima Draw] cbrange (=auto): Farbbereich Liste [min,max]. Globale Option. [Maxima Draw] cbrange (=auto): color bar range, list [min,max]. Global option. cbrange cbrange :

[Maxima Draw] cbtics (=auto): Marken an der Farblegende. Globale Option. [Maxima Draw] cbtics (=auto): color bar tick marks. Global option. cbtics cbtics :

[Maxima Draw] color (=blue): Farbe für Linien, Punkte, Kanten und Text, als Namen oder hexadezimal in der Form RGB "#rrggbb" oder RGBA "#rrggbbaa". A steht für Transparenz. [Maxima Draw] color (=blue): color for lines, points, borders and text, given as name, as RGB "#rrggbb" or as RGBA "#rrggbbaa" with A (alpha) being transparency. color color :

[Maxima Draw] colorbox (=true): Farblegende ohne Beschriftung zeichnen, false: keine Farblegende zeichnen, text: Farblegende mit text als Beschriftung zeichnen. Globale Option. [Maxima Draw] colorbox (=true): draw color scale without label, false: no colorbar, string: draw colorbar with string as label. Global option. colorbox colorbox :

[Maxima Draw3D] contour (=none): Art der Höhenlinien. none: keine, base: auf der xy-Ebene, surface: auf der 3D-Fläche, both: auf xy-Ebene und Fläche, map: auf xy-Ebene und Blickrichtung senkrecht. Globale Option. [Maxima Draw3D] contour (=none): contour lines. none: no contours, base: on xy plane, surface: on 3D surface, both: on xy plane and surface, map: on xy plane plus vertical view. Global option. See also contour_levels. contour contour :

[Maxima Draw3D] contour_levels (=5): Werte für die Höhenlinien. Anzahl oder Liste [min, Δ, max], oder set(L1, L2,...) mit Werten. Globale Option. [Maxima Draw3D] contour_levels (=5): contour levels. number oder list [min, Δ, max], or set(L1, L2,...) of values. Global option. contour_levels contour_levels :

[Maxima Draw] data_file_name (="data.gnuplot"): Kurvendaten für Gnuplot [Maxima Draw] data_file_name (="data.gnuplot"): internal data file name for gnuplot data_file_name data_file_name :

[Maxima Draw] delay (=5) Zeitschritt in animierten gif-Dateien. Nur für originale Maxima(draw2d/3d). Globale Option. [Maxima Draw]  delay (=5): time step in animted gif files. Applies only for native Maxima(draw2d/3d). Global option. delay delay :

[Maxima Draw] dimensions (= 600 x 500): Liste [Breite,Höhe]. Nur für originale Maxima(draw2d/3d). Globale Option. [Maxima Draw] dimensions (= 600 x 50:0): list [width, height]. Applies only for native Maxima(draw2d/3d). Global option. dimensions dimensions :

[Maxima Draw] draw_realpart (=true) Realteil zur Darstellung komplexer Werte verwenden. [Maxima Draw] draw_realpart (=true) use real part for plotting complex values. draw_realpart draw_realpart :

[Maxima Draw] enhanced3d (=none) Farbpalette, none: 3D Flächen als Gitter zeichnen (Steuerung mit color und surface_hide), true: Farbe anhand des z-Werts, Liste  [f(x,y,z), x, y, z]: Farbe anhand der Funktion f, Liste [f(u,v),u,v]: Farbe anhand der Flächenparameter oder Liste [f(k), k ]: Farbe anhand der Punktnummer in points() Objekten. [Maxima Draw3D] enhanced3d (=true) coloring of surfaces by z-value, (control using color und surface_hide), false: draw 3D surfaces as grid, or list [f(x,y,z), x, y, z]: coloring according to function f or list [f(u,v),u,v] or list [f(k), k ] (k being the point counter in points() objects). enhanced3d enhanced3d :

[Maxima Draw2D] error_type (=y) Art der Fehlerbalken in errors():  x, y, xy oder boxes. [Maxima Draw2D] error_type (=y) type of error bars in errors():  x, y, xy or boxes. error_type error_type :

[Maxima Draw] file_name (="maxima_out") Grafik-Ausgabedatei, Endung wird gemäß Ausgabeformat ergänzt. Globale Option. [Maxima Draw] file_name (="maxima_out") output file, extension is set according to format. Global option. Only for experts. file_name file_name :

[Maxima Draw2D] fill_color (=red) Füllfarbe für Objekte polygon() und explicit(). [Maxima Draw2D] fill_color (=red) fill color for polygons and explicit functions y(x). fill_color fill_color :

[Maxima Draw] fill_density (=0) Deckungsgrad der Füllfarbe in bars()-Objekten, zwischen 0 und 1. Für andere Objekte benutzen Sie option color mit der Transparenz aa in "rrggbbaa". [Maxima Draw] fill_density (=0) opacity of the fill color in bars()-objects, 0..1. For other objects use option color with transparency aa in "#rrggbbaa". fill_density fill_density :

[Maxima Draw2D] filled_func (=false): explizite Funktionen y(x) werden nicht gefüllt, true: Füllung bis zur Unterkante des Diagramms, g(x): Füllung zwischen g(x) und y(x). [Maxima Draw2D] filled_func (=false): don't fill explicit functions y(x), true: fill between the next explicit() object and the bottom border of the diagram, g(x): fill between g(x) and the next explicit() object. filled_func filled_func :

[Maxima Draw] gnuplot_file_name (="maxout.gnuplot"): Kommandodatei für Gnuplot. Gobale Option nur für Experten. [Maxima Draw] gnuplot_file_name (="maxout.gnuplot"): name of the temporary gnuplot command file. Global option. Only for experts. gnuplot_file_name gnuplot_file_name :

[Maxima Draw] gnuplot_term (): Ausgabe-Format-Spezifikation (Text nach "set terminal"). Gobale Option nur für Experten. [Maxima Draw] gnuplot_term (): gnuplot terminal options (arguments of "set terminal"). Global option. Only for experts. Use name argument of Draw2D() or Draw3D for format specification. gnuplot_term gnuplot_term :

[Maxima Draw] gnuplot_out_file (=maxplot.xxx) Ausgabedateiname (xxx abhängig vom Format). Gobale Option nur für Experten. [Maxima Draw] gnuplot_out_file (=maxplot.xxx) output file name (xxx depends on terminal). Global option. Only for experts. gnuplot_out_file gnuplot_out_file :

[Maxima Draw] grid (=true): Gitterraster zeichnen, false: kein Gitter zeichnen. Global option. [Maxima Draw] grid (=true): draw xy grid, false: don't draw grid. Global option. grid grid :

[Maxima Draw] head_angle (=45) Pfeilwinkel an vector()-Objekten (halber Öffnungswinkel in °) [Maxima Draw] head_angle (=45): head angle of vector()-objects (angle between border and vector  direction in °) head_angle head_angle :

[Maxima Draw] head_both (=false) oder true: ob bei vector()-Objekten zwei Pfeilspitzen gezeichnet werden. [Maxima Draw] head_both (=false): don't draw a second head of vector() objects, true: draw a second head. head_both head_both :

[Maxima Draw] head_length (=2) Länge der Pfeilspitze bei vector()-Objekten in Einheiten der x-Achse. [Maxima Draw] head_length (=2): head length of vector() objects in units of the x-axis. head_length head_length :

[Maxima Draw] head_type (=filled) Spitzenform bei vector()-Objekten: filled, empty oder nonfilled. [Maxima Draw] head_type (=filled) head type of vector() objects: filled ▲, empty ∆ or nofilled Λ. head_type head_type :

[Maxima Draw] interpolate_color (=false) Farbglättung auf Facetten. true: Optimale Glättung, Liste [n, m] Zahl der Unterteilung. false: Einheitliche Farbe. [Maxima Draw] interpolate_color (=false) color smoothing on facets. true: optimal smoothing, list [n, m] number of subdivisions. false: homogeneous color. interpolate_color interpolate_color :

[Maxima Draw] ip_grid (=Liste [50, 50] ): Primäres Gitter für die Darstellung impliziter Funktionen, als Liste angeben. [Maxima Draw] ip_grid (= list[50, 50] ): primary grid for sampling of implicit functions, two-element list. ip_grid ip_grid :

[Maxima Draw3D] ip_grid_in (= Liste [5, 5] ): Sekundäres Gitter für die Darstellung impliziter Funktionen. [Maxima Draw3D] ip_grid_in (= list [5, 5] ): secondary grid for sampling of implicit functions. ip_grid_in ip_grid_in :

[Maxima Draw] key (=""): Legendeneintrag für das nachfolgende Grafikobjekt. [Maxima Draw] key (=""): legend key for subsequent graphics object. key key :

[Maxima Draw] key_pos (="", entspricht top_right): Legendenposition. Gültige Werte: top_left, top_center, top_right, center_left, center, center_right, bottom_left, bottom_center, bottom_right. Globale Option. [Maxima Draw] key_pos (="", equivalent to top_right): position of the legend. Valid options: top_left, top_center, top_right, center_left, center, center_right, bottom_left, bottom_center, bottom_right. Global option key_pos key_pos :

[Maxima Draw] label_alignment (=center), left oder right: horizontale Ausrichtung von Beschriftungen. [Maxima Draw] label_alignment (=center), left or right: alignment of text labels. label_alignment label_alignment :

[Maxima Draw] label_orientation (=horizontal) oder vertical: Ausrichtung von Texten. [Maxima Draw] label_orientation (=horizontal) or vertical: orientation of text labels. label_orientation label_orientation :

[Maxima Draw] line_type (=solid) Linienart. Alternativen: dots (für alle Formate) oder wenn von Gnuplot unterstützt: dashes, short_dashes, short_long_dashes, short_short_long_dashes. [Maxima Draw] line_type (=solid) line type. Other options: dots (for all formats) or if supported by Gnuplot: dashes, short_dashes, short_long_dashes, short_short_long_dashes. line_type line_type :

[Maxima Draw] line_width (=1) Linienstärke, >0. [Maxima Draw] line_width (=1) line width, >0. line_width line_width :

[Maxima Draw] logcb (=false) oder true: logarithmische Farbskale. Globale Option. [Maxima Draw] logcb (=false) or true: log scale of the colorbar. Global option. logcb logcb :

[Maxima Draw] logx (=false) oder true: logarithmische x-Achse. Globale Option. [Maxima Draw] logx (=false) or true: log scale of x-axis. Global option. logx logx :

[Maxima Draw2D] logx_secondary (=false) oder true: logarithmische zweite x-Achse. Globale Option. [Maxima Draw2D] logx_secondary (=false) or true: log scale of secondary x-axis. Global option. logx_secondary logx_secondary :

[Maxima Draw] logy (=false) oder true: logarithmische y-Achse. Globale Option. [Maxima Draw] logy (=false) or true: log scale of y-axis. Global option. logy logy :

[Maxima Draw2D] logy_secondary (=false) oder true: logarithmische zweite y-Achse. Globale Option. [Maxima Draw2D] logy_secondary (=false) or true: log scale of secondary y-axis. Global option. logy_secondary logy_secondary :

[Maxima Draw] logz (=false) oder true: logarithmische z-Achse. Globale Option. [Maxima Draw] logz (=false) or true: log scale of z-axis. Global option. logz logz :

[Maxima Draw] nticks (=29): Punktezahl für die Kurvenabtastung [Maxima Draw] nticks (=29): number of points for curve sampling (explicit and parametric) nticks nticks :

[Maxima Draw] palette (=color) Standard-Farbpalette, gray: Graustufen, Liste [Farbe1, Farbe2...]: Interpolation über die gegebenen Farben. Globale Option. [Maxima Draw] palette (=color) default color palette, gray: gray levels, or list [color1, color2...]: interpolation over the given set of colors. Global option. palette palette :

[Maxima Draw] point_size (=1) Größe von points()-Symbolen. [Maxima Draw] point_size (=1) size of points()-symbols. point_size point_size :

[Maxima Draw] point_type (=1) Symbol für points()-Objekte, Name oder Kennzahl: none -1, dot 0, plus 1, multiply 2, asterisk 3, square 4, filled_square 5, circle 6, filled_circle 7, up_triangle 8, filled_up_triangle 9, down_triangle 10, filled_dwn_triangle 11, diamant 12, filled_diamant 13 [Maxima Draw] point_type (=1) type of points() objects, name or key number: none -1, dot 0, plus 1, multiply 2, asterisk 3, square 4, filled_square 5, circle 6, filled_circle 7, up_triangle 8, filled_up_triangle 9, down_triangle 10, filled_down_triangle 11, diamant 12, filled_diamant 13 point_type point_type :

[Maxima Draw] points_joined (=false), true oder impulses: Verbindungsart von points()-Objekten [Maxima Draw] points_joined (=false), true or impulses: how to join points points_joined points_joined :

[Maxima Draw] proportional_axes (=none), xy oder xyz: Achsen mit gleicher Skalierung). Globale Option. [Maxima Draw] proportional_axes (=none), xy or xyz: set axes of equal scaling). Global option. proportional_axes proportional_axes :

[Maxima Draw3D] surface_hide (=false) oder true: Ausblendung verdeckter Flächen bei Linienrasterdarstellung. Nur relevant wenn enhanced3D=false. [Maxima Draw3D] surface_hide (=false) or true: handling of hidden lines in surface grids. Only relevant if enhanced2d=false. surface_hide surface_hide :

[Maxima Draw] terminal (=screen) Ausgabeart. screen: Separates Ausgabefenster, png, jpg, gif, eps, svg, pdf, animated_gif: Gnuplot Ausgabeformat. Globale Option. Nur für Experten. Nutzen Sie das Name-Argument von Draw2D()/3D(). [Maxima Draw] terminal (=screen) separate interactive terminal window,  png, jpg, gif, eps, svg, pdf, animated_gif: gnuplot output format. Global option. Only for experts. Use name argument of Draw2D/3D instead. terminal terminal :

[Maxima Draw] title (="") Überschrift für das Diagramm. Globale Option. [Maxima Draw] title (="") headline for the plot. Global option title title :

[Maxima Draw] transform (=none) Koordinatentransformation, für 2D als Liste [f1(x,y), f2(x,y), x, y], für 3D als Liste [f1(x,y), f2(x,y), f3(x, y, z), x, y, z] [Maxima Draw] transform (=none) co-ordinate transformation, for 2D as list [f1(x,y), f2(x,y), x, y], for 3D as list [f1(x,y), f2(x,y), f3(x, y, z), x, y, z] transform transform :

[Maxima Draw] transparent (=false) oder true: ob Rechtecke, Polygone oder Ellipsen transparent sein sollen (bei false werden sie gefüllt). Für echte Transparenz nutzen Sie die Option color mit dem Transparenzwert aa der RGBA Farbspezifikation "#rrggbbaa". [Maxima Draw] transparent (=false) fill objects with border, true: don't fill (make them transparent). For actual transparency use RGBA color "rrggbbaa" with the color option. transparent transparent :

[Maxima Draw] unit_vectors (=false) oder true: Vektoren in originaler Länge oder als Einheitsvektoren zeichnen. [Maxima Draw] unit_vectors (=false) draw vectors in original length, true: draw unit vectors. unit_vectors unit_vectors :

[Maxima Draw] user_preamble (="") Zeichenkette oder Liste von Zeichenketten, die unmittelbar vor dem eigentlichen Diagrammbefehl an Gnuplot übergeben werden. Globale Option. [Maxima Draw] user_preamble (="") string or list of strings, gnuplot commands placed  immediately before the plot commands. Global option user_preamble user_preamble :

[Maxima Draw] view (=(60,30)) Blickrichtung (Zenithwinkel von z aus, Azimutwinkel von x aus). Globale Option. [Maxima Draw] view (=(60,30)) view direction (zenith angle from z, azimut angle from x). Global option. view view :

[Maxima Draw] wired_surface (=false) oder true: Gitternetz auf eingefärbten Flächen anzeigen oder nicht. Globale Option. [Maxima Draw] wired_surface (=false) no grid on colored surfaces, true: draw grid on surfaces. No color control. Global option. wired_surface wired_surface :

[Maxima Draw3D] x_voxel (=10) x-Bereichsteilung für den Marching-Cubes-Algorithmus bei implizit gegebenen Flächen. [Maxima Draw3D] x_voxel (=10) number of x steps for the Marching Cubes algorithm (for implicit 3D functions). Also used for region(). x_voxel x_voxel :

[Maxima Draw3D] y_voxel (=10) y-Bereichsteilung für den  Marching-Cubes-Algorithmus bei implizit gegebenen Flächen. [Maxima Draw3D] y_voxel (=10) number of y steps for the Marching Cube algorithm (for implicit 3D functions). Also used for region(). y_voxel y_voxel :

[Maxima Draw3D] z_voxel (=10) z-Bereichsteilung für den Marching-Cubes-Algorithmus bei implizit gegebenen Flächen. [Maxima Draw3D] z_voxel (=10) number of z steps for the Marching Cube algorithm (for implicit 3D functions). z_voxel z_voxel :

[Maxima Draw] xaxis (=false) oder true: Anzeige der x-Achse. Globale Option. [Maxima Draw] xaxis (=true): draw x-axis. false: don't draw x-axis. Global option xaxis xaxis :

[Maxima Draw] yaxis (=false) oder true: Anzeige der y-Achse. Globale Option. [Maxima Draw] yaxis (=true): draw y-axis. false: don't draw y-axis. Global option yaxis yaxis :

[Maxima Draw3D] zaxis (=false) oder true: Anzeige der z-Achse. Globale Option. [Maxima Draw3D] zaxis (=true): draw x-axis. false: don't draw x-axis. Global option. zaxis zaxis :

[Maxima Draw] xaxis_color (=black) Farbe x-Achse. Globale Option. [Maxima Draw] xaxis_color (=black) color of the x-axis. Global option. xaxis_color xaxis_color :

[Maxima Draw] yaxis_color (=black) Farbe y-Achse. Globale Option. [Maxima Draw] yaxis_color (=black) color of the y-axis. Global option. yaxis_color yaxis_color :

[Maxima Draw3D] zaxis_color (=black) Farbe z-Achse. Globale Option. [Maxima Draw3D] zaxis_color (=black) color of the z-axis. Global option zaxis_color zaxis_color :

[Maxima Draw2D] xaxis_secondary (=false) oder true: Nutzung einer zweiten x-Achse (oben) für die nachfolgenden Objekte. [Maxima Draw2D] xaxis_secondary (=false) or true: use the secondary x-axis (top) for subsequent objects. xaxis_secondary xaxis_secondary :

[Maxima Draw2D] yaxis_secondary (=false) oder true: Nutzung einer zweiten y-Achse (rechts) für die nachfolgenden Objekte [Maxima Draw2D] yaxis_secondary (=false) or true: use the secondary y-axis (right) for subsequent objects yaxis_secondary yaxis_secondary :

[Maxima Draw] xaxis_type (=dots) oder solid: Linienart der x-Achse. Globale Option. [Maxima Draw] xaxis_type (=solid) or dots. Global option. xaxis_type xaxis_type :

[Maxima Draw] yaxis_type (=dots) oder solid: Linienart der y-Achse. Globale Option. [Maxima Draw] yaxis_type (=solid) or dots. Global option. yaxis_type yaxis_type :

[Maxima Draw3D] zaxis_type (=dots) oder solid: Linienart der z-Achse. Globale Option. [Maxima Draw3D] zaxis_type (=solid) or dots. Global option. zaxis_type zaxis_type :

[Maxima Draw] xaxis_width (=1) Linienbreite der x-Achse. Globale Option. [Maxima Draw] xaxis_width (=1). Global option xaxis_width xaxis_width :

[Maxima Draw] yaxis_width (=1) Linienbreite der y-Achse. Globale Option. [Maxima Draw] yaxis_width (=1). Global option yaxis_width yaxis_width :

[Maxima Draw3D] zaxis_width (=1) Linienbreite der z-Achse. Globale Option. [Maxima Draw3D] zaxis_width (=1). Global option. zaxis_width zaxis_width :

[Maxima Draw] xlabel (="") x-Achsenbeschriftung. Globale Option. [Maxima Draw] xlabel (="") label of the x-axis. Global option xlabel xlabel :

[Maxima Draw] ylabel(="") y-Achsenbeschriftung. Globale Option. [Maxima Draw] ylabel (="") label of the y-axis. Global option ylabel ylabel :

[Maxima Draw] zlabel (="") z-Achsenbeschriftung. Globale Option. [Maxima Draw] zlabel (="") label of the z-axis. Global option zlabel zlabel :

[Maxima Draw] xlabel_secondary (="") Beschriftung der zweiten x-Achse. Globale Option. [Maxima Draw] xlabel_secondary (="") label of the secondary x-axis. Global option xlabel_secondary xlabel_secondary :

[Maxima Draw] ylabel_secondary (="") Beschriftung der zweiten y-Achse. Globale Option. [Maxima Draw] ylabel_secondary (="") label of the secondary y-axis. Global option ylabel_secondary ylabel_secondary :

[Maxima Draw] xrange (=auto) oder Liste [min,max]: x-Achsenbereich. Globale Option. [Maxima Draw] xrange (=auto) or list [min,max]: range of the x-axis. Global option xrange xrange :

[Maxima Draw] yrange (=auto) oder Liste [min,max]: y-Achsenbereich. Globale Option. [Maxima Draw] yrange (=auto) or list [min,max]: range of the y-axis. Global option yrange yrange :

[Maxima Draw] zrange (=auto) oder Liste [min,max]: z-Achsenbereich. Globale Option. [Maxima Draw] zrange (=auto) or list [min,max]: range of the z-axis. Global option. zrange zrange :

[Maxima Draw] xrange_secondary (=auto) oder Liste [min,max]: Bereich der zweiten (oberen) x-Achse. Globale Option. [Maxima Draw] xrange_secondary (=auto) or list [min,max]: range of the secondary (top) x-axis. Global option. xrange_secondary xrange_secondary :

[Maxima Draw] yrange_secondary (=auto) oder Liste [min,max]: Bereich der zweiten (rechten) y-Achse. Globale Option. [Maxima Draw] yrange_secondary (=auto) or list [min,max]: range of the secondary (right) y-axis. Global option. yrange_secondary yrange_secondary :

[Maxima Draw] xtics (=auto): automatische x-Achsmarken, none: keine, Zahl: Schrittweite, Liste mit [min, Schritt, max], oder set() von Zahlen: explizite Vorgabe der Zahlenwerte, oder set() von Listen ["text",pos] mit Vorgabe von Beschriftung und Position. Globale Option. [Maxima Draw] xtics (=auto): automatic x ticks, none: no x ticks, number: tick interval, list of [min, step, max], or set() of numbers: explicit tick values, or set() of lists ["text",pos] for spec of position and text. Global option xtics xtics :

[Maxima Draw] ytics (=auto): automatische y-Achsmarken, none: keine, Zahl: Schrittweite, Liste mit [min, Schritt, max], oder set() von Zahlen: explizite Vorgabe der Zahlenwerte, oder set() von Listen ["text",pos] mit Vorgabe von Beschriftung und Position. Globale Option. [Maxima Draw] ytics (=auto): automatic y ticks, none: no y ticks, number: tick interval, list of [min, step, max], or set() of numbers: explicit tick values, or set() of lists ["text",pos] for spec of position and text. Global option. ytics ytics :

[Maxima Draw] ztics (=auto): automatische z-Achsmarken, none: keine, Zahl: Schrittweite, Liste mit [min, Schritt, max], oder set() von Zahlen: explizite Vorgabe der Zahlenwerte, oder set() von Listen ["text",pos] mit Vorgabe von Beschriftung und Position. Globale Option. [Maxima Draw] ztics (=auto): automatic z ticks, none: no x ticks, number: tick interval, list of [min, step, max], or set() of numbers: explicit tick values, or set() of lists ["text",pos] for spec of position and text. Global option. ztics ztics :

[Maxima Draw] xtics_secondary (=auto): automatische Marken an der sekundären (oberen) x-Achse, none: keine, Zahl: Schrittweite, Liste mit [min, Schritt, max], oder set() von Zahlen: explizite Vorgabe der Zahlenwerte, oder set() von Listen ["text",pos] mit Vorgabe von Beschriftung und Position. Globale Option. [Maxima Draw] xtics_secondary (=auto): automatic ticks on the secondary (top) x-axis, none: no ticks, number: tick interval, list of [min, step, max], or set() of numbers: explicit tick values, or set() of lists ["text",pos] for spec of position and text. Global option. xtics_secondary xtics_secondary :

[Maxima Draw] ytics_secondary (=auto): automatische Marken an der sekundären (rechten) y-Achse, none: keine, Zahl: Schrittweite, Liste mit [min, Schritt, max], oder set() von Zahlen: explizite Vorgabe der Zahlenwerte, oder set() von Listen ["text",pos] mit Vorgabe von Beschriftung und Position. Globale Option. [Maxima Draw] ytics_secondary (=auto): automatic ticks on the secondary (right) y-axis, none: no ticks, number: tick interval, list of [min, step, max], or set() of numbers: explicit tick values, or set() of lists ["text",pos] for spec of position and text. Global option. ytics_secondary ytics_secondary :

[Maxima Draw] xtics_axis (=false): x-Achsmarken am Rand, true: an der Achse. Globale Option. [Maxima Draw] xtics_axis (=false): ticks on the boundary, true: ticks on the axis. Global option. xtics_axis xtics_axis :

[Maxima Draw] ytics_axis (=false): y-Achsmarken am Rand, true: an der Achse. Globale Option. [Maxima Draw] ytics_axis (=false): ticks on the boundary, true: ticks on the axis. Global option. ytics_axis ytics_axis :

[Maxima Draw] ztics_axis (=false): z-Achsmarken am Rand, true: an der Achse. Globale Option. [Maxima Draw] ztics_axis (=false): ticks on the boundary, true: ticks on the axis. Global option. ztics_axis ztics_axis :

[Maxima Draw] xtics_secondary_axis (=false): Marken an der sekundaren (oberen) x-Achse am Rand, true: an der Achse. Globale Option. [Maxima Draw] xtics_secondary_axis (=false): ticks on the secondary (top) boundary, true: ticks on the axis. Global option. xtics_secondary_axis xtics_secondary_axis :

[Maxima Draw] ytics_secondary_axis (=false): Marken an der sekundaren (rechten) y-Achse am Rand, true: an der Achse. Globale Option. [Maxima Draw] ytics_secondary_axis (=false): ticks on the secondary (right) boundary, true: ticks on the axis. Global option. ytics_secondary_axis ytics_secondary_axis :

[Maxima Draw] xtics_rotate (=false): x-Achsmarken nicht drehen, true: um 90° drehen. Globale Option. [Maxima Draw] xtics_rotate (=false): horizontal tick labels, true: vertical tick labels. Global option. xtics_rotate xtics_rotate :

[Maxima Draw] ytics_rotate (=false): y-Achsmarken nicht drehen, true: um 90° drehen. Globale Option. [Maxima Draw] ytics_rotate (=false): horizontal tick labels, true: vertical tick labels. Global option. ytics_rotate ytics_rotate :

[Maxima Draw] ztics_rotate (=false): z-Achsmarken nicht drehen, true: um 90° drehen. Globale Option. [Maxima Draw] ztics_rotate (=false): horizontal tick labels, true: vertical tick labels. Global option. ztics_rotate ztics_rotate :

[Maxima Draw] xtics_rotate_secondary (=false): Marken an der sekundären (oberen) x-Achse nicht drehen, true: um 90° drehen. Globale Option. [Maxima Draw] xtics_rotate_secondary (=false): don't rotate ticks of the secondary (top) x-axis, true: rotate by 90°. Global option. xtics_rotate_secondary xtics_rotate_secondary :

[Maxima Draw] ytics_rotate_secondary (=false): Marken an der sekundären (rechten) y-Achse nicht drehen, true: um 90° drehen. Globale Option. [Maxima Draw] ytics_rotate_secondary (=false): don't rotate ticks of the secondary (right) y-axis, true: rotate by 90°. Global option ytics_rotate_secondary ytics_rotate_secondary :

[Maxima Draw] xu_grid (=30) Abtastpunkte in x- oder u-Richtung [Maxima Draw] xu_grid (=30) sampling points in x- or u-direction xu_grid xu_grid :

[Maxima Draw] yv_grid (=30) Abtastpunkte in y- oder v-Richtung [Maxima Draw] yv_grid (=30) sampling points in y- or v-direction yv_grid yv_grid :

[Maxima Draw3D] xyplane (=false): xy-Koordinatenebene automatisch anordnen, Zahl: z-Koordinate. Globale Option. [Maxima Draw3D] xyplane (=false): automatic allocation of the xy-plane, real number: xy-plane intersects the z-axis at this level. Global option. xyplane xyplane :

Objekte

[Maxima Draw2D] bars(b1,b2...) Säulendiagramm, Säulen gegeben durch Listen (x,h,w). Optionen: key, color, fill_color, fill_density und line_width. [Maxima Draw2D] bars(b1,b2...) vertical bars, given as lists [x,h,w]. Options: key, color, fill_color, fill_density and line_width._bars_bars :

[Maxima Draw3D] elevation_grid(Matrix,x0,y0,w,h) Stellt eine Matrix in 3D dar. M_11 bei x=x0,y=y0+h, M_mn bei x=x0+w,y=y0. Optionen:  xu_grid, yv_grid, line_type, key, wired_surface, enhanced3d und color [Maxima Draw3D] elevation_grid(matrix,x0,y0,w,h) Draws a m x n-matrix in 3D. M_11 at x=x0,y=y0+h, M_mn at x=x0+w,y=y0. Options:  xu_grid, yv_grid, line_type, key, wired_surface, enhanced3d and color_1_2_3_4_5 elevation_grid_1_2_3_4_5 elevation_grid :

[Maxima Draw3D] elevation_grid(Matrix,x0,y0,w,h) Stellt eine Matrix in 3D dar. M_11 bei x=x0,y=y0+h, M_mn bei x=x0+w,y=y0. Optionen:  xu_grid, yv_grid, line_type, key, wired_surface, enhanced3d and color [Maxima Draw3D] cylindrical(r(φ,z),z,zmin,zmax,φ,φmin,φmax) Draws a function in cylindrical coordinates. Options: xu_grid, yv_grid, line_type, key, wired_surface, enhanced3d and color._1_2_3_4_5_6_7 cylindrical_1_2_3_4_5_6_7 cylindrical :

[Maxima Draw2D] ellipse(xc,yc,a,b,φ1,φ2) Ellipse, zentriert bei xc, yc mit den Halbachsen a und b, von Startwinkel φ1 und Winkelbreite dφ. In Maxima 5.47 wird die Breite doppelt gezählt. Optionen nticks, transparent, fill_color, border, line_width, line_type, key und color. [Maxima Draw2D] ellipse(xc,yc,a,b,φ1,dφ) plots an ellipse centered at [xc, yc] with horizontal and vertical semi axis a and b, respectively, starting at φ1 with an amplitude dφ. Note that in Maxima 5.47 the amplitude is doubled. Options: nticks, transparent, fill_color, border, line_width, line_type, key and color. #1 #2 #3 #4 #5 #6 ellipse #1 #2 #3 #4 #5 #6 ellipse :

[Maxima Draw2D] errors(e1,e2...) Punkte mit Fehlerbalken, horizontal, vertical oder beide, abhängig von der Option error_type. Argumente für error_type = x: Listen [x, y, xdelta] oder [x, y, xlow, xhigh]. Argumente für error_type = y; Listen [x, y, ydelta] oder [x, y, ylow, yhigh]. Argumente für error_type = xy oder error_type = boxes: Listen [x, y, xdelta, ydelta] oder [x, y, xlow, xhigh, ylow, yhigh]. Optionen: error_type, points_joined, line_width, key, line_type, color, fill_density, xaxis_secondary, and yaxis_secondary [Maxima Draw2D] errors(e1,e2...) Draws points with error bars, horizontally, vertically or both, depending on the value of option error_type. If error_type = x, arguments are lists [x, y, xdelta] or [x, y, xlow, xhigh]. If error_type = y, arguments are lists [x, y, ydelta] or [x, y, ylow, yhigh]. If error_type = xy or error_type = boxes, arguments are lists [x, y, xdelta, ydelta] or [x, y, xlow, xhigh, ylow, yhigh]. Options: error_type, points_joined, line_width, key, line_type, color, fill_density_errors_errors :

[Maxima Draw2D] explicit(f,x,xmin,xmax) zeichnet eine Funktion f von x von xmin bis xmax. Optionen: nticks, adapt_depth, draw_realpart, line_width, line_type, key, filled_func, fill_color und color [Maxima Draw2D] explicit(f,x,xmin,xmax) plots explicit function f, with variable x taking values from xmin to xmax. Options: nticks, adapt_depth, draw_realpart, line_width, line_type, key, filled_func, fill_color and color_1_2_3_4 explicit_1_2_3_4 explicit :

[Maxima Draw3D] explicit(f,x,xmin,xmax,y,ymin,ymax) zeichnet eine Funktion f von x und y im Bereich xmin bis xmax und ymin bis ymax Optionen: draw_realpart, xu_grid, yv_grid, line_type, line_width, key, wired_surface, enhanced3d und color. [Maxima Draw3D] explicit(f,x,xmin,xmax,y,ymin,ymax) plots the explicit function f, with variable x taking values from xmin to xmax and variable y taking values from ymin to ymax. Options: draw_realpart, xu_grid, yv_grid, line_type, line_width, key, wired_surface, enhanced3d, and color. #1 #2 #3 #4 #5 #6 #7 explicit #1 #2 #3 #4 #5 #6 #7 explicit :

[Maxima Draw2D] image(Matrix,x0,y0,w,h)  Farbdarstellung einer m x n Matrix entsprechend der Option palette im Gebiet (x0,y0) bis (x0+w,y0+h) [Maxima Draw2D] image(matrix,x0,y0,w,h)  plots matrix in the rectangular region from vertex (x0,y0) to (x0+w,y0+h) according to global option palette. #1 #2 #3 #4 #5 image #1 #2 #3 #4 #5 image :

[Maxima Draw2D] implicit(f,x,xmin,xmax,y,ymin,ymax) 2D Darstellung einer implizit gegebenen Funktion im angegebenen Variablenbereich (marching squares Algorithmus). Optionen: ip_grid, ip_grid_in, line_width, line_type, key, color [Maxima Draw2D] implicit(f,x,xmin,xmax,y,ymin,ymax) plots the implicit function defined by f, with variable x taking values from xmin to xmax, and variable y taking values from ymin to ymax. Options: ip_grid, ip_grid_in, line_width, line_type, key, color #1 #2 #3 #4 #5 #6 #7 implicit #1 #2 #3 #4 #5 #6 #7 implicit :

[Maxima Draw3D] implicit(f,x,xmin,xmax,y,ymin,ymax,z,zmin,zmax) 3D Darstellung einer implizit gegebenen Funktion im angegebenen Variablenbereich (Marching Cubes Algorithmus). Optionen: x_voxel, y_voxel, z_voxel, ip_grid_in, line_width, line_type, wired_surface, enhanced3D, color [Maxima Draw] [Maxima Draw3D] implicit(f,x,xmin,xmax,y,ymin,ymax,z,zmin,zmax) plots the implicit surface defined by f, with variable x taking values from xmin to xmax, variable y taking values from ymin to ymax and variable z taking values from zmin to zmax. This object implements the marching cubes algorithm. Options: x_voxel, y_voxel, z_voxel, line_width, line_type, key, wired_surface, enhanced3d,and color #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 implicit #1 #2 #3 #4 #5 #6 #7 #8 #9 #10 implicit :

[Maxima Draw2D and 3D] label(list) Beschriftung, im 2D gegeben als Liste (text,x,y), im 3D als Liste (text,x,y,z), spezielle Optionen: color, label_alignment, label_orientation [Maxima Draw2D and 3D] label(list) text label specified in 2D as list [text,x,y], in 3D as list [text,x,y,z], Options: color, label_alignment, label_orientation_label_label :

[Maxima Draw2D] parametric(fx,fy,p,pmin,pmax) parametrisch gegebenen Funktion. Optionen: nticks, line_width, line_type, key, color, enhanced3d [Maxima Draw2D] parametric(fx,fy,p,pmin,pmax) plots the parametric function fx, fy  with parameter p taking values from pmin to pmax. Options: nticks, line_width, line_type, key, color, enhanced3d #1 #2 #3 #4 #5 parametric #1 #2 #3 #4 #5 parametric :

[Maxima Draw3D] parametric(fx,fy,fz,p,pmin,pmax) Parametrische Funktion, beschrieben durch drei Koordinatenfunktionen des Parameters p im gegebenen Bereich von pmin bis pmax. Optionen: nticks, line_width, line_type, key, color, enhanced3d [Maxima Draw3D] parametric(fx,fy,fz,p,pmin,pmax) parametric function, described by three coordinate functions of parameter p, taking values from pmin to pmax. Options: nticks, line_width, line_type, key, color, enhanced3d #1 #2 #3 #4 #5 #6 parametric #1 #2 #3 #4 #5 #6 parametric :

points(matrix) Punkte, 2D: n x 2 oder 2 x n -> n Punkte bei (x,y) oder 1 x n oder n x 1 -> n Punkte bei (index,y). 3D: n x 3 oder 3 x n -> Punkte bei (x,y,z). Spezielle Optionen: points_joined, point_type, point_size [Maxima Draw2D/3D] [Maxima Draw2D and 3D] points(matrix) 2D: n x 2 or 2 x n -> n points at (x,y) or 1 x n or n x 1 -> n points at (index,y). 3D: n x 3 or 3 x n -> points at (x,y,z). Specific options: points_joined, point_type, point_size, enhanded #1 points #1 points :

[Maxima Draw2D] points(lx,ly) Punkte, gegeben durch zwei Listen der x- und y-Koordinaten. Spezielle Optionen: points_joined, point_type, point_size [Maxima Draw2D] [Maxima Draw2D] points(lx,ly) points given by two lists, special options: points_joined, point_type, point_size #1 #2 points #1 #2 points :

[Maxima Draw3D] points(lx,ly,lz) zeichnet Punkte, gegeben durch drei Listen, spezielle Optionen: points_joined, point_type, point_size [Maxima Draw3D] points(lx,ly,lz) points given by three lists, pecial options: points_joined, point_type, point_size #1 #2 #3 points #1 #2 #3 points :

[Maxima Draw2D] polar(r,φ,φmin,φmax) zeichnet Funktionen, die in Polarkoordinaten gegeben sind (Radius r als Funktion des Winkels φ). Spezielle Optionen: key, nticks, line_width, line_type, color [Maxima Draw2D] polar(r,φ,φmin,φmax) draws functions given in polar co-ordinates (radius r as function of angle φ). Special options: key, nticks, line_width, line_type, color #1 #2 #3 #4 polar #1 #2 #3 #4 polar :

[Maxima Draw2D] polygon(matrix)  Polygon durch die als n x 2 Matrix gegebenen Punkte. Spezielle Optionen: transparent, fill_color, border, line_width, key, line_type color [Maxima Draw2D] polygon(matrix)  polygon defined by matrix (each row one point). Special options: transparent, fill_color, border, line_width, key, line_type color #1 polygon #1 polygon :

[Maxima Draw2D]  polygon(lx,ly)  Zeichnet ein Polygon durch die als x- und y-Listen gegebenen Punkte. Spezielle Optionen: transparent, fill_color, border, line_width, key, line_type color [Maxima Draw2D]  polygon(lx,ly)  polygon defined by two lists. Special options: transparent, fill_color, border, line_width, key, line_type, color #1 #2 polygon #1 #2 polygon :

[Maxima Draw2D/3D] quadrilateral(l1,l2,l3,l4) Viereck, gegeben durch Listen der Eckkoordinaten 2D: [x,y] oder 3D: [x,y,z]. Spezielle Optionen: transparent, fill_color, border, line_width, key, line_type, color, enhanced3D (nur 3D) [Maxima Draw2D/3D] quadrilateral(l1,l2,l3,l4) quadrilateral given by lists  of vertex coordinates: [x,y] in 2D or [x,y,z] in 3D. Special options: transparent, fill_color, border, line_width, key, line_type, color, enhanced3D (3D only) #1 #2 #3 #4 quadrilateral #1 #2 #3 #4 quadrilateral :

[Maxima Draw2D] rectangle(l1,l2) Rechteck gegeben durch Koordinatenlisten [x,y] gegenüberliegender Ecken. Spezielle Optionen: transparent, fill_color, border, line_width, key, line_type, color [Maxima Draw2D] rectangle(l1,l2) specified by lists [x,y] of opposite corners. Special options: transparent, fill_color, border, line_width, key, line_type, color #1 #2 rectangle #1 #2 rectangle :

[Maxima Draw2D] region(expr,x,xmin,xmax,y,ymin,ymax) Füllt das Gebiet wo expr wahr (true) ist im Bereich von xmin, xmax, ymin, ymax. Optionen: fill_color, key, x_voxel, y_voxel [Maxima Draw2D] region(expr,x,xmin,xmax,y,ymin,ymax) Fills the region where expr is true in the domain given by xmin, xmax, ymin, ymax. Options: fill_color, key, x_voxel, y_voxel #1 #2 #3 #4 #5 #6 #7 region #1 #2 #3 #4 #5 #6 #7 region :

[Maxima Draw2D] region(expr,x,xmin,xmax,y,ymin,ymax) Füllt das Gebiet wo expr wahr (true) ist im Bereich von xmin, xmax, ymin, ymax. Optionen: fill_color, key, x_voxel, y_voxel [Maxima Draw3D] spherical(r, a, mina, maxa, z, minz, maxz) plots function r(a, z) defined in spherical coordinates, with azimuth a taking values from mina to maxa and zenith z taking values from minz to maxz. Options: xu_grid, yv_grid, line_type, key, wired_surface, enhanced3d, and color. #1 #2 #3 #4 #5 #6 #7 spherical #1 #2 #3 #4 #5 #6 #7 spherical :

[Maxima Draw2D/3D] triangle(l1,l2,l3)  Dreieck, gegeben durch Koordinatenlisten [x,y] (2D) oder [x,y,z] (3D) der Ecken. Spezielle Optionen: transparent, fill_color, border, line_width, key, line_type, color [Maxima Draw2D/3D] triangle(l1,l2,l3)  given by co-ordinate lists [x,y] (2D) or [x,y,z] (3D) of the corners.Options: transparent, fill_color, border, line_width, key, line_type, color #1 #2 #3 triangle #1 #2 #3 triangle :

[Maxima Draw3D]  tube(fx,fy,fz,fr,p,pmin,pmax)  Röhre, gegeben durch Mittellinie mit fx,fy,fz und den Radius fr als Funktionen des Parameters p. Spezielle Optionen:  xu_grid, yv_grid, line_type, line_width, key, wired_surface, enhanced3d, color, capping. [Maxima Draw3D]  tube(fx,fy,fz,fr,p,pmin,pmax)  tube, given by functions fx,fy,fz of the centerline and radius function fr of the parameter p from pmin to pmax. Special options:  xu_grid, yv_grid, line_type, line_width, key, wired_surface, enhanced3d, color, capping. #1 #2 #3 #4 #5 #6 #7 tube #1 #2 #3 #4 #5 #6 #7 tube :

[Maxima Draw2D/3D]  vector(l1,l2)  Pfeil,  gegeben durch Koordinatenlisten (x,y) (2D) oder (x,y,z) (3D) der Endpunkte. Spezielle Optionen:  head_both, head_length, head_angle, head_type, line_width, line_type, key color. [Maxima Draw2D/3D]  vector(l1,l2)  given by co-ordinate lists [x,y] (2D) or [x,y,z] (3D) of the end points. Spezielle Optionen:  head_both, head_length, head_angle, head_type, line_width, line_type, key color. #1 #2 vector #1 #2 vector :

Sonstige

[Maxima]  set(e1, e2,...) Maxima set (Liste in geschweiften Klammern) [Maxima]  set(e1, e2,...) Maxima set (in Maxima this is a list in curly braces)_set_set :

[Maxima] args(expr) Liste der Argumente von expr [Maxima] args(expr) list of the top level arguments of expr. Extracts lines from matrices._args_args :

[Maxima] apply(f, Liste) Macht die Elemente der Liste zu Argumenten von f. apply(f,args(matrix)) wandelt eine Matrix in Argumente einer Funktion um -> f(row1, row2,...) [Maxima] apply(f, list) applies the elements of list as arguments to f. apply(f,args(matrix)) converts a matrix into arguments of a function -> f(row1, row2,...)_args_args :

[Maxima] true true :

[Maxima] false false :

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 terminal=pdfcairo file_name="C:/Users/kraska/AppData/Roaming/SMath/extensions/plugins/44011c1e-5d0d-4533-8e68-e32b5badce41/GnuPlot/feqm0nhr" font="Arial" font_size=12 title="Wirkungsgrad" contour_levels=5 contour=base background_color="#fefefe" enhanced3d = true xu_grid=40 yv_grid=40 xlabel="p_1 in atm" ylabel="p_2 in atm" zlabel="z" "set term pdfcairo enhanced size 5.51, 3.7" "set encoding utf8" "set style line 100 lc rgb 'grey' lt -1 lw 0.1" "set grid xtics ls 100" "set grid ytics ls 100" "set pm3d lighting depthorder base" "set view 54, 246, 1, 1" plot3D SAMPLE PLOT Wirkungsgrad Custom Disable 4095 12 Disable Arial Enable base 5 #fefefe Enable Enable color 40 40 Custom 529 355 Interactive C:/Users/kraska/AppData/Roaming/SMath/extensions/plugins/44011c1e-5d0d-4533-8e68-e32b5badce41/GnuPlot/feqm0nhr pdf Disable p_1 in atm p_2 in atm z solid solid black black 1 1 Enable Enable Enable -5 5 -5 5 44.5638970854504 49.6246534111202 Disable Disable Disable Enable Enable Disable Disable Disable Disable 10 10 10 246 54 1 1 Interactive Disable MouseX1 MouseY1 MouseW1 Disable Azimut1 Zenit1 Disable MinX1 MaxX1 Disable MinY1 MaxY1 Disable MinZ1 MaxZ1 false false false Enable Disable key ≡ M % / p.1.min atm / p.2.max atm / p.1.max p.1.min - atm / p.2.min p.2.max - atm / elevation_grid xyplane 47 ≡ interpolate_color true ≡ contour_levels 48.4 48.6 48.5 set ≡ 5 1 sys